Was it raw POS tagged data or just raw data? can you share the code /
process you used?
--
Itamar Syn-Hershko
http://code972.com | @synhershko <https://twitter.com/synhershko>
Freelance Developer & Consultant
Lucene.NET committer and PMC member
On Thu, Jan 29, 2015 at 3:34 PM, Mark Harwood <
mark.harw...@elasticsearch.com> wrote:
> I've built one before from raw data but you need:
> 1) a *lot* of data
> 2) a unique ID per person
> 3) some noise/variation in the names recorded for each person
>
> The input is of this form:
>
> personID recorded_name
> === =
> 1 Rob
> 1 Robert
> 1 Bob
> 2 Dave
> 2 David
> 2 Alice
> ...
>
> The output is a weighted graph of name<->variant e.g Robert== Bob with a
> strong confidence rating.
> Using this I know not just real names but also typos e.g. that "Janes" is
> more likely to be "James" than "Jane" (a common typo due to key locations
> on keyboard).
>
>
>
>
> On Thursday, January 29, 2015 at 5:28:33 AM UTC, David Kemp wrote:
>>
>> I am looking for synonym dictionaries of person names that I can use with
>> the Elasticsearch synonym analyser.
>> e.g. dictionaries that map "Ted" to "Edward", and "Bill" to "William".
>> I am curious to know what others are using.
>> So far I have found these two possible sources:
>>
>> https://code.google.com/p/nickname-and-diminutive-names-
>> lookup/downloads/list
>> https://github.com/DallanQ/Names/wiki/Name-variant-files
>>
>> And perhaps
>> http://www.behindthename.com
>>
>> Thanks,
>> David
>>
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